Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Forensic facial examiners versus super-recognizers: Evaluating behavior beyond accuracy

Published

Author(s)

Carina Hahn, Liansheng Tang, Amy Yates, P. Jonathon Phillips

Abstract

We evaluated the detailed, behavioral properties of face matching performance in two specialist groups: forensic facial examiners and super-recognizers. Both groups compare faces to determine identity with high accuracy and outperform the general population. Typically, facial examiners are highly trained; super-recognizers rely on natural ability. We found distinct behaviors between these two groups. Examiners used the full 7-point identity judgment scale (−3: "different"; +3: "same"). Super-recognizers' judgments clustered toward highly confident decisions. Examiners' judgments for same- and different-identities were symmetric across the scale midpoint (0); super-recognizers' judgments were not. Examiners showed higher identity judgment agreement than super-recognizers. Despite these qualitative differences, both groups showed insight into their own accuracy: more confident people and those who rated the task to be easier tended to be more accurate. Altogether, we show to better understand and interpret judgments according to the nature of someone's facial expertise, evaluations should assess more than accuracy.
Citation
Applied Cognitive Psychology

Keywords

facial forensics, facial identification, facial proficiency, forensic facial examiner, super-recognizer

Citation

Hahn, C. , Tang, L. , Yates, A. and Phillips, P. (2022), Forensic facial examiners versus super-recognizers: Evaluating behavior beyond accuracy, Applied Cognitive Psychology, [online], https://doi.org/10.1002/acp.4003, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=934238 (Accessed December 14, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created September 25, 2022, Updated November 29, 2022